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Real-Time Assessment of Causal Attribution Shift and Stay Between Two Successive Tests of Movement Aids
Integrative Psychological and Behavioral Science ( IF 1.156 ) Pub Date : 2021-01-09 , DOI: 10.1007/s12124-020-09592-7
Takumi Ohashi 1 , Makiko Watanabe 2 , Yuma Takenaka 3 , Miki Saijo 1
Affiliation  

The development of welfare assistive devices for frail elderly people has attracted significant attention for its effort to improve the quality of life and reduce the burden on caregivers. However, it is challenging to conduct multiple user tests because of the significant burden on the elderly; thus, we need efficient ways to extract insight through different approaches. In this study, we aim to elucidate real-time transitions in users’ emotions and achievement motivation while using such a device. We synthesize an utterance analysis method based on attribution theory, in which all users’ utterances are attributed to four categories (ability, effort, task difficulty, and luck) that follow the developed coding rules. Knowing the transitions in causal attribution allows us to extract salient experiences for users, especially by extracting shifts from them and analyzing why the shift occurred and what exactly was happening before and after the shift. If only salient user experiences can be referenced from the aggregate data, useful information can be extracted in a short time to improve system characteristics and the environment. We discussed the validity and reliability of the proposed method by conducting a user test of an electric-assisted four-wheeled cycle for frail elderly people in Kakegawa city in Shizuoka, Japan. We also succeeded in marking the points that need attention, which is about 33% of the total amount of utterance data (1626 utterances), and thus confirmed the potential of the proposed method. Future research should examine how the developed methodology can help designers improve assistive device development, as well as how it can contribute to other fields such as education and social assistance.



中文翻译:

对连续两次运动辅助测试之间的因果归因转移和停留的实时评估

体弱老人福利辅助器具的研制因其努力提高生活质量和减轻照顾者的负担而备受关注。然而,由于老年人负担过重,进行多用户测试具有挑战性;因此,我们需要有效的方法来通过不同的方法提取洞察力。在这项研究中,我们旨在阐明使用这种设备时用户情绪和成就动机的实时转变。我们综合了一种基于归因理论的话语分析方法,其中所有用户的话语都按照制定的编码规则被归为四个类别(能力、努力、任务难度和运气)。了解因果归因的转变使我们能够为用户提取显着体验,尤其是通过从中提取变化并分析变化发生的原因以及变化前后究竟发生了什么。如果只能从聚合数据中引用显着的用户体验,则可以在短时间内提取有用的信息,以改善系统特性和环境。我们通过对日本静冈挂川市体弱老人的电动四轮自行车进行用户测试,讨论了所提出方法的有效性和可靠性。我们还成功标记了需要注意的点,约占话语数据总量(1626 条话语)的 33%,从而证实了所提出方法的潜力。未来的研究应该研究开发的方法如何帮助设计人员改进辅助设备的开发,

更新日期:2021-01-10
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